A Real Time Ultra-Wideband Location System for Smart Healthcare

Driven by the demand of intelligent monitoring in rehabilitation centers or hospitals, a high accuracy real-time location system based on UWB (ultra-wideband) technology was proposed. The system measures precise location of a specific person, traces his movement and visualizes his trajectory on the screen for doctors or administrators. Therefore, doctors could view the position of the patient at any time and find them immediately and exactly when something emergent happens. In our design process, different algorithms were discussed, and their errors were analyzed. In addition, we discussed about a , simple but effective way of correcting the antenna delay error, which turned out to be effective. By choosing the best algorithm and correcting errors with corresponding methods, the system attained a good accuracy. Experiments indicated that the ranging error of the system is lower than 7 cm, the locating error is lower than 20 cm, and the refresh rate exceeds 5 times per second. In future works, by embedding the system in wearable IoT (Internet of Things) devices, it could provide not only physical parameters, but also the activity status of the patient, which would help doctors a lot in performing healthcare.

Implementation of Edge Detection Based on Autofluorescence Endoscopic Image of Field Programmable Gate Array

Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Fractal Analysis on Human Colonic Pressure Activities based on the Box-counting Method

The colonic tissue is a complicated dynamic system and the colonic activities it generates are composed of irregular segmental waves, which are referred to as erratic fluctuations or spikes. They are also highly irregular with subunit fractal structure. The traditional time-frequency domain statistics like the averaged amplitude, the motility index and the power spectrum, etc. are insufficient to describe such fluctuations. Thus the fractal box-counting dimension is proposed and the fractal scaling behaviors of the human colonic pressure activities under the physiological conditions are studied. It is shown that the dimension of the resting activity is smaller than that of the normal one, whereas the clipped version, which corresponds to the activity of the constipation patient, shows with higher fractal dimension. It may indicate a practical application to assess the colonic motility, which is often indicated by the colonic pressure activity.